title: Development and validation of a claims-based prediction model for COPD severity.
abstract: BACKGROUND
  Administrative claims are an important data source for COPD research but lack a validated measure of patient COPD severity, which is an important determinant of treatment and outcomes.
  
  
  METHODS
  Patients with ≥1 diagnosis of COPD and spirometry results from 01/2004-05/2011 were identified from an electronic health records database linked to healthcare claims. Patients were classified into 3 COPD severity groups based on spirometry and Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines: GOLD-Unclassified, Mild/Moderate, and Severe/Very Severe. A multinomial logistic regression model was constructed using claims data from 3 months before and after (observation period) the most recent spirometry (index date) to categorize patient COPD severity. A random selection of 90% of patients in each severity level was selected to build the model, and the remaining 10% were used as a validation sample. Model predictions were evaluated for sensitivity, specificity, accuracy, and concordance.
  
  
  RESULTS
  Among 2028 COPD patients who met sample selection criteria, 886, 683, and 459 patients were in the GOLD-Unclassified, Mild/Moderate, and Severe/Very Severe categories, respectively. The final model included age, sex, comorbidities (such as pulmonary fibrosis and diabetes), COPD-related resource utilization (such as oxygen use), and all-cause healthcare utilization. In the validation sample, the model correctly predicted COPD severity for 62.7% of all patients (accuracy for predicting GOLD-Unclassified: 73.5%; Mild/Moderate: 70.6%; Severe/Very Severe: 81.4%) with kappa = 0.41.
  
  
  CONCLUSIONS
  The prediction model was developed using clinically measured COPD severity to provide researchers an approach to classify patients using claims data when clinical measures are not available.
authors.affiliation: Analysis Group, Inc., New York, NY, USA. Electronic address: dmacaulay@analysisgroup.com.
authors.forename: Dendy
authors.initials: D
authors.lastname: Macaulay
authors.forename: Shawn X
authors.initials: SX
authors.lastname: Sun
authors.forename: Rachael A
authors.initials: RA
authors.lastname: Sorg
authors.forename: Sherry Y
authors.initials: SY
authors.lastname: Yan
authors.forename: Gourab
authors.initials: G
authors.lastname: De
authors.forename: Eric Q
authors.initials: EQ
authors.lastname: Wu
authors.forename: Paul F
authors.initials: PF
authors.lastname: Simonelli
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D015897:Comorbidity; D016208:Databases, Factual; D003695:Delivery of Health Care / Q000706:statistics & numerical data; D005260:Female; D005541:Forced Expiratory Volume / Q000502:physiology; D006801:Humans; D007345:Insurance Claim Review; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D010414:Pennsylvania / Q000453:epidemiology; D029424:Pulmonary Disease, Chronic Obstructive / Q000175:diagnosis* / Q000453:epidemiology / Q000503:physiopathology / Q000628:therapy; D012720:Severity of Illness Index; D013147:Spirometry; D014797:Vital Capacity / Q000502:physiology
keywords: BMI; COPD; COPD severity; Claims-based; EHR; ER; FEV(1); FVC; GHP; GHS; GOLD; Geisinger Health Plan; Geisinger Health System; Global Initiative for Chronic Obstructive Lung Disease; ICD-9; International Classification of Diseases, Ninth revision; Prediction model; body mass index; chronic obstructive pulmonary disease; electronic health record; emergency room; forced expiratory volume for one second; forced vital capacity